The impact of data aggregation on the performance of wireless sensor networks

Akkaya, Kemal; Demirbaş, Murat; Aygün, Ramazan

doi:10.1002/wcm.454

Cited by 78 publications

(55 citation statements)

References 30 publications

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“…In this analysis we have excluded the cost of determining optimal aggregation tree (e.g. Minimum Steiner Tree is an NP-Complete problem [Akkaya et al 2008]) assuming that the WSN is static. In dynamic WSN it could o↵set the benefits of aggregation.…”

Section: Discussionmentioning

confidence: 99%

Compression in wireless sensor networks

Razzaque

Bleakley

Dobson

2013

ACM Trans. Sen. Netw.

151

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Wireless sensor networks (WSNs) are highly resource constrained in terms of power supply, memory capacity, communication bandwidth, and processor performance. Compression of sampling, sensor data, and communications can significantly improve the e ciency of utilization of three of these resources, namely power supply, memory and bandwidth. Recently, there have been a large number of proposals describing compression algorithms for WSNs. These proposals are diverse and involve di↵erent compression approaches. It is high time that these various individual e↵orts are put into perspective and a more holistic view taken. In this article, we take a step in that direction by presenting a survey of the literature in the area of compression and compression frameworks in WSNs. A comparative study of the various approaches is also provided. In addition, open research issues, challenges and future research directions are highlighted.

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Section: Discussionmentioning

confidence: 99%

Compression in wireless sensor networks

Razzaque

Bleakley

Dobson

2013

ACM Trans. Sen. Netw.

151

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show abstract

“…In these conditions, error control and secure data aggregation is critical for WSNs. However data aggregation operation in WSNs improves the bandwidth and energy utilization, but on the other performance metrics such as delay, accuracy, faulttolerance and security, it may have negative affect 3 . There is a strong conflict between security and data aggregation protocols 4 .…”

Section: Advantages Of the Proposed Schemementioning

confidence: 99%

Reliable Wireless Sensor Networks by Using Redundant Residue Number System

Barati¹,

Movaghar²,

Sabaei³

et al. 2013

Proceedings of the 2013 International Conference on Advanced Computer Science and Electronics Information

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-In this paper, a new scheme using redundant residue number system is proposed for decreasing the total consumption power and thus, increasing the lifetime, and also to reach error controllability to improve reliability of received data and therewith to obtain improvement in end-to-end delay in wireless sensor networks. The proposed scheme employs the new moduli set . Moreover, to complete the new scheme, an efficient reverse converter in both terms of conversion delay and hardware saving is designed and implement based on mixed radix conversion algorithm.Index Terms -Redundant Residue Number System, Reverse Converter, Mixed-Radix-Conversion, Wireless Sensor Networks I . IntroductionWireless sensor networks technologies with a large number of multifunctional low-power sensor nodes have received tremendous attention because of wide applications in today's world 1 . In such as networks, two critical issues are energy conservation and reliability in data delivery 2 . In this paper, using redundant residue number system in wireless sensor network applications is proposed for solving the said problems.Redundant residue number systems (RRNSs) are appropriate for use in wireless sensor network, because of 3 factors: 1) strong error controllability, 2) low energy consumption, 3) run-time operations.In RRNS, by considering some modulus, instead of sending number , the remainders of are transmitted, so fewer packets are sending and power consumption is reduced. Receiver using a reverse converter decodes the received packets and recovers the original message and then, detects and corrects error, if occurred.The most important part of any RNS design is moduli set selection, because it has direct effect on system's speed, its dynamic range and area utilization of reverse converter. The reverse converter is responsible to convert back the received data from RNS to conventional representation and is the most complex of any residue to number system design.In this paper, the new residue number system moduli set is proposed and an efficient reverse converter is designed and implement base on the new moduli set that is suitable for wireless sensor networks with low power resources. II. Advantages Of The Proposed SchemeBecause the absence of carry propagation between the arithmetic blocks results in high speed processing, RNS is high speed. This feature is beneficial for wireless sensor networks that need to run-time applications. RNS needs to reduce power. Because of smaller words are transmitted in RNS representation. Thus smaller arithmetic units are realized in the RNS processors that reduce the switching activities in each channel. This results in reduction in the dynamic power, since the dynamic power is directly proportional to switching activities. Therewith, RNS has parallel operations that reduce power consumption and delay simultaneously.Moreover, noted that WSNs have wide applications and maybe deployed in a hostile environment, such as battlefield. In these conditions, error control and secure data aggregation...

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“…Wireless sensor is collection of hundreds or thousands of sensor node, thus it has various applications such as habitat and environment monitoring, fire detection, intrusion detection, biological hazard detection and intrusion detection [2]. Normally sensor nodes are low-powered sensing devices with, less computational capacity, limited memory and communication resources [1].…”

Section: Introductionmentioning

confidence: 99%

Review on: Data Aggregation and Dynamic Routing in Wireless Sensor Network

Somkuwar¹,

Kamble²

2014

IJCA

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A wireless sensor network (WSN) has important applications such as monitoring temperature, humidity, level, speed, remote environmental monitoring and target tracking. Main critical issue in sensor network is maximization of network lifetime. All sensor nodes are required large amount of energy to send and receive data; also it depends upon distance between two nodes. Therefore with the help of Data aggregation technique we reduce the size of data. In wireless sensor network's (WSN's) nodes need less power for processing as compared to send data. Second technique is to reduce amount of energy to send data by using shortest path that can be achieve with the help of dynamic routing. Our proposed technique is attribute aware data aggregation. Attributes means the identifier of sampled data by different sensors node such as humidity sensors, temperature sensors etc., should be gathered together. Attribute-aware Data Aggregation mechanism which can collect packets with same attribute as much as possible and hence improve the efficiency of data aggregation. This aim can't be achieved by static routing technique of data aggregation mechanisms since they construct routes before transmitting the sampled data and thus cannot dynamically forward packets in response to the variation of packets at intermediate. Therefor we use potential-based dynamic routing scheme to transfer data into network.

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The impact of data aggregation on the performance of wireless sensor networks

Cited by 78 publications

References 30 publications

Compression in wireless sensor networks

Compression in wireless sensor networks

Reliable Wireless Sensor Networks by Using Redundant Residue Number System

Review on: Data Aggregation and Dynamic Routing in Wireless Sensor Network

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